Experimental results on item-based algorithm for independent domain collaborative filtering
Proceedings Of The 4th International Conference On Automated Solutions For Cross Media Content And Multi-channel Distributin, Number 10.1109/AX, page 87--92 - november 2008
A research analysis on item-based algorithms for collaborative filtering is presented. The aim of the presented activity was to find a configuration of an item-based algorithm capable of providing good results but also independent from the data set. Four data sets were used for the algorithm validation: Netflix, MovieLens, BookCrossing, and Jester. The experimentation involved the following aspects: similarity computation, size of the neighbourhood, prediction computation, minimum number of co-rated items. Results were evaluated in terms of Root Mean Squared Error (RMSE). The result of the activity is an independent domain configuration for an item-based algorithm which produced satisfactory results with most of the above mentioned data sets.
Références BibTex
@InProceedings{CL08a,
author = {Clemente, M.},
title = {Experimental results on item-based algorithm for independent domain collaborative filtering},
booktitle = {Proceedings Of The 4th International Conference On Automated Solutions For Cross Media Content And Multi-channel Distributin},
number = {10.1109/AX},
series = {IEEE Computer Society},
pages = {87--92},
month = {november},
year = {2008},
editor = {Paolo Nesi and Kia Ng and Jaime Delgado},
note = {isbn: 978-0-7695-3406-0
idxproject: ?},
url = {http://ieeexplore.ieee.org/search/freesrchabstract.jsp?arnumber=4688054\&isnumber=4688033\&punumber=4688032\&k2dockey=4688054@ieeecnfs\&query=(item-based+algorithms)\%3Cin\%3Emetadata\&pos=0
}